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Record W4399453467 · doi:10.7202/1111610ar

Repenser le travail social au Québec : comment intégrer les préoccupations environnementales dans la pratique ?

2024· article· fr· W4399453467 on OpenAlexaffabout
Sue-Ann MacDonald, Érick Rioux, Rosemary Carlton, Lena Dominelli, Émmanuelle Khoury

Bibliographic record

VenueIntervention · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsMinistère de l’Emploi et de la Solidarité Sociale (Québec)Université de Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Au Québec, les liens entre la pratique du travail social et la crise écologique, ainsi que les impacts de celle-ci sur les populations en situation de vulnérabilité, sont des avenues qui commencent à être explorées dans la recherche. Cet article s’inscrit dans ce mouvement et expose notre analyse issue d’un projet de recherche exploratoire auprès de praticiennes en travail social. Il sera question d’examiner leurs points de vue sur les connexions qu’elles établissent entre leur pratique et l’écologie. Notre analyse montre que les participantes reconnaissent la pertinence de leur profession face à la crise écologique, mais que leur contexte de pratique ainsi que la façon dont l’environnement et la nature sont conceptualisés à même la profession peuvent être des facteurs contraignants pour l’écologisation du travail social. Cet article s’inscrit donc dans une invitation collective à réfléchir au travail social d’aujourd’hui et de demain devant la nécessité d’intégrer de manière plus significative les préoccupations environnementales dans la pratique professionnelle.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.296

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0200.013
Scholarly communication0.0060.003
Open science0.0020.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0090.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.336
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2024
Admission routes2
Has abstractyes

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